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The 2017 US Frontiers of Engineering was hosted by United Technologies Research Center in East Hartford, Connecticut, September 25-27. About 100 outstanding engineers under the age of 45 met for an intensive 2-1/2 day symposium to discuss cutting-edge developments in four areas: Machines That Teach Themselves, Energy Strategies to Power Our Future, Unraveling the Complexity of the Brain, and Mega-Tall Buildings and Other Future Places of Work. The goal of the Frontiers of Engineering program is to bring together engineers from all engineering disciplines and from industry, universities, and federal labs to facilitate cross-disciplinary exchange and promote the transfer of new techniques and approaches across fields in order to sustain and build US innovative capacity.
LIST OF SESSIONS
Chair: Robert Braun, University of Colorado Boulder
MACHINES THAT TEACH THEMSELVES
Session chair: Rajan Bhattacharyya, HRL Laboratories
Reinforcement Learning and Learning to Promote Learning
Emma Brunskill, Stanford University
Can Machines Spot Diseases Faster than Expert Humans?
Suchi Saria, Johns Hopkins University
Humans and Computers Working Together to Measure Machine Learning Interpretability
Jordan Boyd-Graber, University of Maryland
ENERGY STRATEGIES TO POWER OUR FUTURE
Session co-chairs: Katherine Dykes, National Renewable Energy Laboratory, and Jeremy Munday, University of Maryland
Agile Fractal Systems: Re-Envisioning Power System Architecture
Tim Heidel, National Rural Electric Cooperative Association
Big Data and Analytics for Wind O&M: Opportunities, Trends, and Challenges in the Industrial Internet
Bouchra Bouqata, GE Global Research Center
Across Dimensions and Scales: How Imaging and Machine Learning Will Help Design Tomorrow's Energy Conversion Devices
Mariana Bertoni, Arizona State University
Wireless Charging of Electric Vehicles
Khurram Afridi, University of Colorado Boulder
UNRAVELING THE COMPLEXITY OF THE BRAIN
Session co-chairs: Xue Han, Boston University, and Maryam Shanechi, University of Southern California
Technologies to Interface with the Brain for Recording and Stimulation
Ellis Meng, University of Southern California
Brain-Machine Interface Paradigms for Neuroscience and Clinical Translation
Jose Carmena, University of California, Berkeley
Machine Learning for Biomedical Science
Konrad Körding, University of Pennsylvania
Efficient Feature Extraction and Classification Methods in Neural Interfaces
Azita Emami, California Institute of Technology
MEGA-TALL BUILDINGS AND OTHER FUTURE PLACES OF WORK
Session co-chairs: Maria Paz Gutierrez, University of California, Berkeley, and Marija Trcka, United Technologies Corp.
The Evolution of Elevators: Digital Interaction, Physical Human Interface, Intuitive Behavior and Mega-tall Buildings
Stephen Nichols, Otis
Supertall Timber: Functional Natural Materials for High-Rise Structures
Michael Ramage, University of Cambridge
Applications of Insights from Biology and Mathematics to the Design of Material Structures
Jenny Sabin, Cornell University